Motion Discontinuity-Robust Controller for Steerable Mobile Robots

(IEEE RA-L 2017): Steerable wheeled mobile robots (SWMR) are able to perform arbitrary 3D planar trajectories, only after initializing the steer joint vector to the proper values. These robots employ fully steerable conventional wheels. Hence, they have higher load carrying capacity than their holonomic counterparts, and as such are preferable for industrial applications. Industrial setups nowadays are being prepared for the emerging field of human-robot collaboration/cooperation. Such field is highly dynamic, due to fast moving human workers, sharing the operation space. This imposes the need for human safe trajectory generators, that can lead to frequent halts in motion, re-planning, and to sudden, discontinuous changes in the position of the robot’s instantaneous center of rotation (ICR). Indeed, this requires steer joint reconfiguration to the newly computed trajectory. This issue is almost ignored in the literature, and motivates this work. The authors propose a new ICR-based kinematic controller, that is capable of handling discontinuity in commanded velocity, while respecting the maximum joint performance limit. This is done by formulating a quadratic optimization problem with linear constraints in the 2D ICR space. The controller is also robust against representation and kinematic singularities. It has been tested successfully on the Neobotix-MPO700 industrial mobile robot.

Parsimonious Kinematic Control of Highly Redundant Robots

(IEEE RA-L, 2016): When a robot is highly redundant in comparison to the task to be executed, current control techniques are not “economic” in the sense that they demand, most of the time unnecessarily, all the joints to move. Such behavior can be undesirable for some applications. In this direction, this work proposes a new control paradigm based on linear programming that intrinsically provides a parsimonious control strategy, that is, one in which few joints move. In addition to a formal stability proof, the paper presents simulation and experimental results on the HOAP-3 humanoid robot. Finally, a comparison is made with a least-square method based on the pseudoinverse of the task Jacobian, showing that the proposed method indeed uses fewer joints than the classic one.

Kinematic modeling and control for human-robot cooperation considering different interaction roles (Robotica, 2015)
This paper presents a novel approach for the description of physical human-robot interaction (pHRI) tasks that involve two-arm coordination, and where tasks are described by the relative pose between the human hand and the robot hand. We develop a unified kinematic model that takes into account the human-robot system from a holistic point of view, and we also propose a kinematic control strategy for pHRI that comprises different levels of shared autonomy. Since the kinematic model takes into account the complete human-robot interaction system and the kinematic control law is closed loop at the interaction level, the kinematic constraints of the task are enforced during its execution. Experiments are performed in order to validate the proposed approach, including a particular case where the robot controls the human arm by means of functional electrical stimulation (FES), which may potentially provide useful solutions for the interaction between assistant robots and impaired individuals (e.g., quadriplegics and hemiplegics).

For intuitive human-robot collaboration, the robot must quickly adapt to the human behavior. To this end, we propose a multimodal sensor-based control framework, enabling a robot to recognize human intention, and consequently adapt its control strategy. Our approach is marker-less, relies on a Kinect and on an on-board camera, and is based on a unified task formalism. Moreover, we validate it in a mock-up industrial scenario, where human and robot must collaborate to insert screws in a flank.

A human’s center of mass (CoM) trajectory is useful to evaluate the dynamic stability during daily life activities such as walking and standing up. To estimate the subject specific CoM position in the home environment, we make use of a statically equivalent serial chain (SESC) developed with a portable measurement system. In this paper we implement a constrained Kalman filter to achieve an online parameter estimation of the SESC parameters while accounting for the human body bilateral symmetry. This results in constraining SESC parameters to be consistent with the human skeletal model used. Kinect is used as a markerless motion capture system for measuring limb orientations while the Wii board is used to measure the subject’s center of pressure (CoP) during the identification phase. CoP measurements and Kinect data were recorded for five able-bodied subjects. The recorded data was then given to the proposed recursive algorithm to identify the parameters of the SESC online.